Fig. 1: Schematic diagram of the bottom-up construction of the whole-brain modeling framework (top row) and the corresponding signals simulated across the various scales (bottom row).
From: A computational approach to evaluate how molecular mechanisms impact large-scale brain activity
Microscale: a point-neuron model is selected to describe the activity of individual neurons, representing different cellular types with specific neuroreceptors and characterized by distinct firing patterns—ranging from RS cells (Exc, excitatory, blue) with adaptive firing rates to FS cells (Inh, inhibitory, red). Mesoscale: based on experimental data of brain microcircuits, we connect the single neurons to build spiking neural networks (high-dimensional mesoscale) from which biologically grounded mean-field models are derived to describe collective dynamics (low-dimensional mesoscale); here νext represents an external input. Macroscale: SC data are integrated into the framework to build large-scale networks of mean-field models to perform whole-brain simulations, allowing the exploration of emergent properties at this scale (for instance, responsiveness to external stimulation). Figure created with BioRender.com.
